Changed the organismQuantityType to dwc:preparations based on the…

… comment in Issue #7.  Added a precision function, but I'm not sure it will work as intended, since it won't account for rounding in whole numbers.

Also checked the issue regarding collection dates.  I've fixed the `startOfYear`/`endOfYear` issue, based on comments in Issue #7, but some dates in Neotoma do appear to show false precision, reporting multiple collection dates on the first of the year, or month.  While these dates are unlikely, they represent the information within Neotoma.  My feeling is that they should be retained.

functionalized_run.R

@@ -5,6 +5,13 @@ library(tidyr)
 
 datasets <- neotoma::get_dataset()
 
+# A function to check decimal precision:
+# `x` - a vector or a single numeric value.
+prec <- function(x, minmax = 'min'){
+
+}
+
+
 test_dwc_export <- function(x){
 
   cat(paste0('Testing: ',x$dataset.meta$dataset.id, '_test_', x$dataset.meta$dataset.type, '\n'))
@@ -174,10 +181,14 @@ test_dwc_export <- function(x){
     }
   }
 
+  # Start of year/End of year refers to the dates of collection.  Should be NA if no collection date is
+  # reported, otherwise, should be the specific date of collection.
   # This should tell us whether or not the collection year was a leap year.  Unfortunately, many records
   # do not have a collection date.  If this is the case, I'm not sure what we do. . . 
-  eoy <- data.frame(startDayOfYear = ifelse(is.na(query_out$eventDate), NA, 1),
-                    endDayOfYear   = ifelse(as.numeric(format(as.POSIXct(query_out$eventDate), '%Y')) %% 100 %% 4 == 0, 366, 365))
+  eoy <- data.frame(startDayOfYear = ifelse(is.na(query_out$eventDate), NA, 
+                                            as.numeric(strftime(query_out$eventDate, format = '%j'))),
+                    endDayOfYear   = ifelse(is.na(query_out$eventDate), NA, 
+                                            as.numeric(strftime(query_out$eventDate, format = '%j'))))
 
   query_out$sampleSizeUnit[query_out$sampleSizeUnit %in% 'NISP'] <- "Number of Identified Samples"
   query_out$sampleSizeUnit[query_out$sampleSizeUnit %in% 'MNI'] <- "Minimum Number of Individuals"
@@ -253,7 +264,7 @@ test_dwc_export <- function(x){
                                                         query_out$AnalysisUnitID, '-', 
                                                         query_out$TaxonID),
                         recordedBy             = query_out$ContactName,
-                        organismQuantityType   = ifelse(query_out$Element_Full == "", NA, query_out$Element_Full),
+                        "dwc:preparations"     = ifelse(query_out$Element_Full == "", NA, query_out$Element_Full),
                         occurrenceStatus       = "present",
                         associatedReferences   = ifelse(regexpr("Neotoma Paleoecological", pubs) > -1, NA, pubs),
                         eventID                = paste0("AnalysisUnit_",query_out$eventID),
@@ -287,7 +298,7 @@ test_dwc_export <- function(x){
                                                         query_out$lonE, " ", 
                                                         query_out$latS, ", ",
                                                         query_out$lonE, ", ",
-                                                        query_out$latN))"),
+                                                        query_out$latN, "))"),
                         footprintSRS           = paste0('GEOGCS["GCS_WGS_1984",DATUM["D_WGS_1984",',
                                                         'SPHEROID["WGS_1984",6378137,298.257223563]],',
                                                         'PRIMEM["Greenwich",0],UNIT["Degree",',